Udemy - Applied Statistics and Probability for Data Science - Pyt...

Files:

• Get Bonus Downloads Here.url (0.2 KB)
~Get Your Files Here ! 1 - Foundations of Statistics
• 1. Introduction.mp4 (65.0 MB)
• 1. Introduction_Resource_1 1 Introduction to Statistics Understanding Data and Datasets xlsx.xlsx (13.2 KB)
• 2. Exploring Variables Using Examples.mp4 (45.7 MB)
• 2. Exploring Variables Using Examples_Resource_1 2 Exploring Variables Using Telecom Industry Examples xlsx.xlsx (14.0 KB)
• 3. Quantitative Variables Concepts and Applications.mp4 (49.7 MB)
• 3. Quantitative Variables Concepts and Applications_Resource_1 3 Quantitative Variables Concepts and Applications xlsx.xlsx (16.3 KB)
10 - Bayes' Theorem and Predictive Analytics
• 35. Bayes' Theorem Overview.mp4 (17.3 MB)
• 36. Predicting Customer Churn.mp4 (50.8 MB)
• 36. Predicting Customer Churn_Resource_10 2 Predicting Customer Churn xlsx.xlsx (36.9 KB)
• 37. Implementing Bayes’ Theorem in Python.mp4 (23.4 MB)
• 38. Use cases Bayes Theorem.mp4 (20.7 MB)
11 - Inferential Statistics and Hypothesis Testing
• 39. Inferential Statistics Overview.mp4 (35.4 MB)
• 40. Forecasting Data Usage with Inferential Methods.mp4 (17.7 MB)
• 41. Introduction to Hypothesis Testing.mp4 (84.0 MB)
• 42. Understanding t Tests and Their Variants.mp4 (42.2 MB)
• 43. Step by Step Performing a Two Sample t Test.mp4 (15.4 MB)
• 44. Use Case Predicting 5G Data Speeds Using t Tests.mp4 (47.2 MB)
2 - Python Basics for Analytics
• 4. Python Basics for Data Analysis (Handson).mp4 (54.1 MB)
• 4. Python Basics for Data Analysis (Handson)_Resource_2 1 Python Basics for Data Analysis Handson ipynb.bin (2.7 KB)
• 5. Loop function in Python.mp4 (32.8 MB)
• 5. Loop function in Python_Resource_2 2 Loop function in Python ipynb.bin (1.2 KB)
• 6. Using Conditional Statements.mp4 (36.9 MB)
• 6. Using Conditional Statements_Resource_2 3 Using Conditional Statements to Detect Network Congestion ipynb.bin (1.1 KB)
• 7. Data Visualization.mp4 (50.5 MB)
• 7. Data Visualization_Resource_2 4 Data Visualization Analyzing Network Performance ipynb.bin (34.4 KB)
3 - Descriptive Statistics Measures of Central Tendency
• 10. Statistical Calculations in Excel and Python.mp4 (25.6 MB)
• 11. Real World Use Cases Central Tendency.mp4 (19.3 MB)
• 8. Understanding Central Tendency.mp4 (39.1 MB)
• 8. Understanding Central Tendency_Resource_3 1 Measures of Central Tendency Python ipynb.bin (2.0 KB)
• 9. Example Analyzing Call Duration Data.mp4 (26.0 MB)
• 9. Example Analyzing Call Duration Data_Resource_3 2 Measures of Central Tendency xlsx.xlsx (12.2 KB)
4 - Descriptive Statistics Understanding Data Dispersion
• 12. Dispersion Metrics Range Variance and Standard Deviation.mp4 (19.8 MB)
• 12. Dispersion Metrics Range Variance and Standard Deviation_Resource_4 1 Data Dispersion Python ipynb.bin (2.7 KB)
• 13. Example Call Duration Data for Dispersion Analysis.mp4 (41.1 MB)
• 13. Example Call Duration Data for Dispersion Analysis_Resource_4 2 Understanding Data Dispersion xlsx.xlsx (12.6 KB)
• 14. Excel and Python for Dispersion Calculations.mp4 (30.9 MB)
• 15. Applications of Dispersion Metrics.mp4 (26.3 MB)
5 - Descriptive Statistics Visualizing Data
• 16. Data Visualization Techniques.mp4 (22.0 MB)
• 16. Data Visualization Techniques_Resource_5 1 Visualizing Telecom Data Excel xlsx.xlsx (25.5 KB)
• 17. Practical Visualizing Call Duration Datasets.mp4 (29.5 MB)
• 17. Practical Visualizing Call Duration Datasets_Resource_5 2 Visualizing Telecom Data Python ipynb.bin (52.9 KB)
• 18. Creating Visuals in Excel.mp4 (19.3 MB)
• 19. Creating Visuals in Python.mp4 (20.8 MB)
6 - Introduction to Probability
• 20. Probability Concepts.mp4 (29.4 MB)
• 21. Permutations and Combinations Simplified.mp4 (30.7 MB)
• 22. Telecom Case Study Spectrum Band combinations.mp4 (27.9 MB)
• 23. Probability Distribution& its types.mp4 (35.4 MB)
7 - Normal Distribution
• 24. Normal Distribution & its properties.mp4 (48.0 MB)
• 25. Case Study Analyzing Daily Call Durations.mp4 (26.8 MB)
• 25. Case Study Analyzing Daily Call Durations_Resource_7 2 Analyzing Daily Call Durations ipynb.bin (28.5 KB)
• 26. Z Scores Predicting User Call Behavior.mp4 (21.6 MB)
8 - Binomial Distribution in Action
• 27. Binomial Distribution & its properties.mp4 (32.8 MB)
• 27. Binomial Distribution & its properties_Resource_8 1 Binomial Distribution Excel xlsx.xlsx (28.5 KB)
• 28. Predicting Call Quality Using Binomial Models.mp4 (18.4 MB)
• 28. Predicting Call Quality Using Binomial Models_Resource_8 2 Binomial Distribution Python ipynb.bin (17.0 KB)
• 29. Excel and Python Implementation.mp4 (99.9 MB)
• 30. Applications of Binomial Distribution.mp4 (21.0 MB)
9 - Poisson Distribution
• 31. Poisson Distribution & its properties.mp4 (32.7 MB)
• 31. Poisson Distribution & its properties_Resource_9 1 Poisson Distribution Excel xlsx.xlsx (15.9 KB)
• 32. Modelling Dropped calls with Poisson Distribution.mp4 (13.1 MB)
• 32. Modelling Dropped calls with Poisson Distribution_Resource_9 2 Poisson Distribution Python ipynb.bin (26.1 KB)
• 33. Practical Poisson Calculations in Excel and Python.mp4 (52.9 MB)
• 34. Use Cases Poisson Distribution.mp4 (24.0 MB)
• Bonus Resources.txt (0.1 KB)